Full Stack Engineer - Data Quality
Build and maintain full-stack systems that ingest and clean e-commerce data (ads, screenshots, emails) using TypeScript, SQL, and AI tools to ensure accuracy and reliability for competitive-intelligence clients.
- Compensation
- Not disclosed
- Location
- Canada
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Full time
- Experience
- 3+ years
- Category
- Fullstack
- Posted
Skills
Must have
- Upper-intermediate to fluent speaking and writing English. Able to have a real-time conversation.
- 5+ years of full-time hands‑on Software Development experience.
- 4+ years of full‑time hands‑on Advanced SQL experience.
- 3+ years of full‑time hands‑on Typescript experience.
- 3+ years of full‑time Data Warehousing experience.
- 3+ years of full‑time hands‑on ETL/Data Pipeline experience.
- Advanced SQL skills and the ability to diagnose and resolve data issues.
- Data warehousing and ETL experience (BigQuery, Snowflake, Redshift, Databricks etc).
- Proficiency in TypeScript and full‑stack development.
- Experience working with event‑driven workflow platforms like Inngest.
- A detail‑oriented, thorough, and methodical approach to problem‑solving.
- Familiarity with AI development tools (Cursor, Google Antigravity) and a knack for working quickly and efficiently.
- A “put out the fire” mentality to find quick resolutions to data issues / outages impacting our customers.
- Ability to build close working relationships with our data providers and data ingestion partners.
Nice to have
- Experience with proxies or anti-bot techniques.
- Bachelor’s degree in Computer Science or equivalent demonstrated ability.
Full description
Join to apply for the Full Stack Engineer - Data Quality role at Right Balance ®
Headquartered in Los Angeles, California, Right Balance provides top-tier technology talent for innovative companies in the US. We’re in the top 50 companies to watch in LA.
Our client is an AI-driven competitive intelligence platform built for modern e-commerce brands. They provide real-time visibility into market shifts by tracking hundreds of thousands of brands, retailers, and marketplaces across categories and channels. Their platform delivers insights on pricing, promotions, creative strategy, merchandising, and overall site experience, helping brands make faster and smarter decisions. Backed by experienced ecommerce operators and strong funding, they’re building a category-defining product at the intersection of AI and commerce intelligence.
The Role
Our client is looking for a highly detail-oriented full-stack engineer to join their team with a strong focus on data quality. In this role, you’ll be the go-to expert for ensuring that all 1st party (customer) and 3rd party data they ingest - whether it’s screenshots, emails, Google Ads, or any other data source - is accurate, complete, and reliably collected.
This role will also see you deployed to work directly with data engineers at key customer accounts, helping them strategize on the data they need to solve their business challenges.
Responsibilities
- Data Quality Management: Identify gaps or inconsistencies in incoming data. This includes developing robust monitoring processes to detect missing screenshots, incomplete email data, gaps in ad records, and the data quality of our integrations into our customers' infrastructure including Shopify, GA4 and Klaviyo.
- Hands-On Problem Solving: Once data issues are identified, you’ll dive into our TypeScript codebase to implement fixes, ensuring that the data pipeline is smooth and robust.
- Full-Stack Development: Work as a full-stack engineer, not only troubleshooting data quality issues but also enhancing and maintaining the systems that process our data with a focus on driving data processing cost efficiencies.
- Investigative Mindset: Approach problems like a forensics data detective - digging into the “why” behind inconsistencies and leaving no stone unturned until the data is pristine.
- AI and Automation: Use AI tools to streamline your workflow, and be comfortable leveraging automation to improve data quality processes.
- Proxies and Anti-Bot Expertise: If you have experience dealing with anti-bot mechanisms or using proxies, that’s a huge plus.